BUG: Regression from 2.1 -> 2.2: df.to_dict produces int instead of timestamp

[behrenhoff]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
df = pd.DataFrame(data={"a": [pd.Timestamp(100)]})
d = df.to_dict(orient="list")

assert d["a"] == [pd.Timestamp(100)]

Issue Description

The assertion fails in pandas 2.2, while it works in pandas 2.1.x

Instead, pandas 2.2 returns [100], i.e. int instead of Timestamp.

Expected Behavior

No dtype change.

Installed Versions

INSTALLED VERSIONS

commit : e86ed37
python : 3.10.12.final.0
python-bits : 64
OS : Linux
OS-release : 6.5.0-15-generic
Version : #15~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Jan 12 18:54:30 UTC 2
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : de_DE.UTF-8
LOCALE : de_DE.UTF-8

pandas : 2.1.1
numpy : 1.26.1
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 59.6.0
pip : 23.3.1
Cython : 3.0.4
pytest : 7.4.3
hypothesis : None
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : 3.1.9
lxml.etree : 4.9.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.16.1
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.0
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.0
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.3
sqlalchemy : 2.0.22
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
zstandard : 0.21.0
tzdata : 2023.3
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report. Result from a git bisect:

commit 18315c5830459535ea8471e66e82fafa4c538e08
Author: taytzehao 
Date:   Sat Sep 2 00:55:05 2023 +0800

    #50990 Increase to_dict('list') performance (#54824)

cc @taytzehao

[behrenhoff]

👍 Thanks a lot for the quick fix!

[mroeschke]

Thanks for reporting! It really helps the project out